entrenar 0.5.6

Training & Optimization library with autograd, LoRA, quantization, and model merging
Documentation
# Docker Compose for Jaeger - OpenTelemetry Backend
#
# LLaMA Training Observability Stack
# Part of Phase 4 (Tracing & Observability) - entrenar spec
#
# Usage:
#   docker-compose -f docker-compose-jaeger.yml up -d
#   docker-compose -f docker-compose-jaeger.yml down
#
# Access Jaeger UI: http://localhost:16686
# OTLP gRPC endpoint: localhost:4317
# OTLP HTTP endpoint: localhost:4318

version: '3.8'

services:
  jaeger:
    image: jaegertracing/all-in-one:latest
    container_name: entrenar-jaeger
    restart: unless-stopped
    environment:
      # Collector endpoints
      - COLLECTOR_OTLP_ENABLED=true
      - COLLECTOR_ZIPKIN_HOST_PORT=:9411

      # Span storage
      - SPAN_STORAGE_TYPE=memory

      # Memory limits (adjust for production)
      - MEMORY_MAX_TRACES=10000

      # Sampling strategy
      - SAMPLING_STRATEGIES_FILE=/etc/jaeger/sampling_strategies.json

    ports:
      # Jaeger UI
      - "16686:16686"

      # OTLP gRPC (for renacer --otlp-endpoint)
      - "4317:4317"

      # OTLP HTTP
      - "4318:4318"

      # Jaeger collector (Thrift)
      - "14268:14268"

      # Jaeger agent (Thrift compact)
      - "6831:6831/udp"

      # Zipkin
      - "9411:9411"

    volumes:
      # Optional: Custom sampling strategies
      - ./jaeger-sampling.json:/etc/jaeger/sampling_strategies.json:ro

    networks:
      - entrenar-observability

    healthcheck:
      test: ["CMD", "wget", "--spider", "-q", "http://localhost:16686"]
      interval: 10s
      timeout: 5s
      retries: 3
      start_period: 10s

    labels:
      - "com.entrenar.service=jaeger"
      - "com.entrenar.description=OpenTelemetry tracing backend"

networks:
  entrenar-observability:
    driver: bridge
    name: entrenar-observability

# Optional: Add Prometheus for metrics (future enhancement)
# Optional: Add Grafana for dashboards (future enhancement)